Multiperspective Representation of Internal Controls in Business Processes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The internal control process, which is designed to help an organization accomplish specific control objectives, is one of the most important processes, as it can determine whether or not the organization is in compliance with its internal or external requirements. Internal controls emerge from different perspectives. Currently, experts view and act on one control perspective at a time, which creates inefficiencies and duplication. This software engineering research is aimed at proposing a multiperspective framework for representing internal controls, in order to obtain a centralized and comprehensive view of all internal control mechanisms. To carry out this research, we also needed to represent the many different stakeholder perspectives of internal controls. Based on a literature review of mathematical and psychological analysis, we searched for the most suitable multiperspective representation of internal controls, and assessed the many representation options using the AHP (analytical hierarchical process) sensitivity analysis approach. This approach has been applied to a study group which has been called to answer to a questionnaire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it